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2008/9 Catalogue
Library Recommendation
 

Summary
January 2007, Vol. 8, No. 1, Pages 101-111 , DOI 10.2217/14622416.8.1.101
(doi:10.2217/14622416.8.1.101)

Special Report
Predicting risk of breast cancer recurrence using gene-expression profiling
Michail Ignatiadis1 & Christine Desmedt1
1Free University of Brussels, Functional Genomics and Translational Research Unit, Jules Bordet Institute, 125 Bld de Waterloo, 1000 Brussels, Belgium.
Author for correspondence



The molecular profiling of breast tumors using the powerful microarray technology has uncovered the molecular heterogeneity of breast tumors and has offered novel insight into breast tumorigenesis. The estrogen receptor (ER) has been shown to be the most important discriminator dichotomizing breast cancer into two main subsets. At the same time, proliferation, as captured by the recently developed Genomic Grade Index (GGI) has been found to be the most important prognostic factor in breast cancer, far beyond ER status. Interestingly, this index encompasses a significant portion of the predictive power of many published prognostic signatures. The challenge now is to integrate all the prognostic gene signatures available to date towards a comprehensive genomic fingerprint of the primary tumor. In the future, we should be able to offer individualized treatment to our patients based on a clinical decision-making algorithm that takes into account the clinicopathological parameters, the genomic profile of the primary tumor, the presence of micrometastatic cells and pharmacogenetic data for drug response.

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Cited by

Erik S. Knudsen, Karen E. Knudsen. (2008) Tailoring to RB: tumour suppressor status and therapeutic response. Nature Reviews Cancer 8:9, 714-724
Online publication date: 1-Oct-2008.
CrossRef
Michail Ignatiadis, Vassilis Georgoulias, Dimitris Mavroudis. (2008) Circulating tumor cells in breast cancer. Current Opinion in Obstetrics and Gynecology 20:1, 55-60
Online publication date: 1-Mar-2008.
CrossRef
 

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Authors:
Michail Ignatiadis
Christine Desmedt
Keywords:
breast cancer
gene-expression profile
genomics
molecular classification
prediction
prognosis
proliferation